Field notes on building with agents and humans
How to put agents to work without handing them the keys, how to write a standard every agent follows, and how teams get more done while a person approves what matters. Written for the people doing the work.
What we write about
Supervising agents
Keeping AI fast and safe at the same time.
Standards and approvals
Designing the steps and approvals that earn their place.
The runtime for agents
Triggers, sandboxes, and validation in practice.
CI/CD for agents
What changes when agents open most of the pull requests.
Observability
Reading conclusions instead of noise.
Team practice
How planning, code, and operations come together.
Field notes, newest first.
Real release notes and practitioner write-ups only. No fabricated dates, no filler.
The 10-ticket rule: when to use Auto-Play (and when not to)
Auto-Play transforms how teams process large batches of work. But it is not always the right choice. Here is a practical framework for deciding when batch execution fits and when manual control serves better.
The knowledge hierarchy: how your AI gets smarter over time
Four levels of agent instructions cascade from organization to project to team to developer. Every execution compounds institutional knowledge. Here is how the hierarchy works.
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